Next-generation video content will feature a high spatial resolution, a high frame rate, and high dimensionality of scene representation. Processing such contents will result in a tremendous increase in terms of a memory storage, a memory access rate, and a processing power. Therefore, there is a need to design a coding tool for processing the next generation video content more efficiently.
In particular, a graph is a form of data representation that is useful for describing relationships between pixels. A graph-based signal processing method has been used which expresses the relation between the pixels as the graph and processes a video signal based on the graph. In this graph-based signal processing, each signal sample represents a vertex, and the relationship between the signals is represented by graph edges with positive weights. Such a graph may be used to generalize concepts such as sampling, filtering, and transformation, etc.
Therefore, a more efficient graph-based signal processing method is required not only in the field of video compression but also in many applications.